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Interactive Visualization for Fostering Trust in ML (Dagstuhl Seminar 22351) Chau, Polo Endert, Alex Keim, Daniel A. Oelke, Daniela accountability artificial intelligence explainability fairness interactive visualization machine learning responsibility trust understandability The use of artificial intelligence continues to impact a broad variety of domains, application areas, and people. However, interpretability, understandability, responsibility, accountability, and fairness of the algorithms' results - all crucial for increasing humans' trust into the systems - are still largely missing. The purpose of this seminar is to understand how these components factor into the holistic view of trust. Further, this seminar seeks to identify design guidelines and best practices for how to build interactive visualization systems to calibrate trust. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Polo Chau and Alex Endert and Daniel A. Keim and Daniela Oelke 2023 Is Part Of Dagstuhl Reports, Volume 12, Issue 8 (2023) Article Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/DagRep.12.8.103 urn:nbn:de:0030-drops-177161 https://drops.dagstuhl.de/entities/document/10.4230/DagRep.12.8.103 eng https://creativecommons.org/licenses/by/4.0/legalcode